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caitianchi 2024-05-23 20:00:45 +08:00
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10
examples/minicpmv/README.md
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@ -6,14 +6,14 @@ make
make minicpmv-cli
python ./examples/minicpmv/minicpmv-surgery.py -m ../MiniCPM-V-2_5
python ./examples/minicpmv/minicpmv-convert-image-encoder-to-gguf.py -m ../MiniCPM-V-2_5 --llava-projector ../MiniCPM-V-2_5/llava.projector --output-dir ../MiniCPM-V-2_5/ --image-mean 0.5 0.5 0.5 --image-std 0.5 0.5 0.5
python ./examples/minicpmv/minicpmv-convert-image-encoder-to-gguf.py -m ../MiniCPM-V-2_5 --minicpmv-projector ../MiniCPM-V-2_5/minicpmv.projector --output-dir ../MiniCPM-V-2_5/ --image-mean 0.5 0.5 0.5 --image-std 0.5 0.5 0.5
python ./convert.py ../MiniCPM-V-2_5/model --outtype f16 --vocab-type bpe
./minicpmv-cli -m ../MiniCPM-V-2_5/model/ggml-model-f16.gguf --mmproj ../MiniCPM-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg -p "What is in the image?"
./minicpmv-cli -m ../MiniCPM-V-2_5/model/model-8B-F16.gguf --mmproj ../MiniCPM-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg -p "What is in the image?"
# or run quantize int4 version
./quantize ../MiniCPM-V-2_5/model/ggml-model-f16.gguf ../MiniCPM-V-2_5/model/ggml-model-Q4_K_M.gguf Q4_K_M
./minicpmv-cli -m ../MiniCPM-V-2_5/model/ggml-model-Q4_K_M.gguf --mmproj ../MiniCPM-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.6 --top-p 0.8 --top-k 100 --repeat-penalty 1.0 --image xx.jpg -p "What is in the image?"
./quantize ../MiniCPM-V-2_5/model/model-8B-F16.gguf ../MiniCPM-V-2_5/model/ggml-model-Q4_K_M.gguf Q4_K_M
./minicpmv-cli -m ../MiniCPM-V-2_5/model/ggml-model-Q4_K_M.gguf --mmproj ../MiniCPM-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg -p "What is in the image?"
# or run in interactive mode
./minicpmv-cli -m ../MiniCPM-V-2_5/model/ggml-model-Q4_K_M.gguf --mmproj ../MiniCPM-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.6 --top-p 0.8 --top-k 100 --repeat-penalty 1.0 --image xx.jpg -i
./minicpmv-cli -m ../MiniCPM-V-2_5/model/ggml-model-Q4_K_M.gguf --mmproj ../MiniCPM-V-2_5/mmproj-model-f16.gguf -c 4096 --temp 0.7 --top-p 0.8 --top-k 100 --repeat-penalty 1.05 --image xx.jpg -i
```

14
examples/minicpmv/clip.cpp
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@ -75,7 +75,7 @@ static std::string format(const char * fmt, ...) {
#define KEY_DESCRIPTION "general.description"
#define KEY_HAS_TEXT_ENC "clip.has_text_encoder"
#define KEY_HAS_VIS_ENC "clip.has_vision_encoder"
#define KEY_HAS_LLAVA_PROJ "clip.has_llava_projector"
#define KEY_HAS_LLAVA_PROJ "clip.has_minicpmv_projector"
#define KEY_USE_GELU "clip.use_gelu"
#define KEY_N_EMBD "clip.%s.embedding_length"
#define KEY_N_FF "clip.%s.feed_forward_length"
@ -526,7 +526,7 @@ struct clip_vision_model {
struct clip_ctx {
bool has_text_encoder = false;
bool has_vision_encoder = false;
bool has_llava_projector = false;
bool has_minicpmv_projector = false;
struct clip_vision_model vision_model;
projector_type proj_type = PROJECTOR_TYPE_MLP;
@ -606,7 +606,7 @@ static ggml_cgraph * clip_image_build_graph(clip_ctx * ctx, const clip_image_f32
const int batch_size = imgs->size;
if (ctx->has_llava_projector) {
if (ctx->has_minicpmv_projector) {
GGML_ASSERT(batch_size == 1);
}
@ -1124,10 +1124,10 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1, s
idx = gguf_find_key(ctx, KEY_HAS_LLAVA_PROJ);
if (idx != -1) {
new_clip->has_llava_projector = gguf_get_val_bool(ctx, idx);
new_clip->has_minicpmv_projector = gguf_get_val_bool(ctx, idx);
}
GGML_ASSERT(new_clip->has_llava_projector); // see monatis/clip.cpp for image and/or text encoding for semantic search
GGML_ASSERT(new_clip->has_minicpmv_projector); // see monatis/clip.cpp for image and/or text encoding for semantic search
GGML_ASSERT(new_clip->has_vision_encoder);
GGML_ASSERT(!new_clip->has_text_encoder);
@ -1137,7 +1137,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1, s
if (verbosity >= 1) {
LOG_TEE("%s: text_encoder: %d\n", __func__, new_clip->has_text_encoder);
LOG_TEE("%s: vision_encoder: %d\n", __func__, new_clip->has_vision_encoder);
LOG_TEE("%s: llava_projector: %d\n", __func__, new_clip->has_llava_projector);
LOG_TEE("%s: llava_projector: %d\n", __func__, new_clip->has_minicpmv_projector);
LOG_TEE("%s: model size: %.2f MB\n", __func__, model_size / 1024.0 / 1024.0);
LOG_TEE("%s: metadata size: %.2f MB\n", __func__, ggml_get_mem_size(meta) / 1024.0 / 1024.0);
}
@ -1939,7 +1939,7 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
}
int batch_size = imgs->size;
if (ctx->has_llava_projector) {
if (ctx->has_minicpmv_projector) {
GGML_ASSERT(batch_size == 1); // TODO: support multiple images
}